An information classification system that classifies information is known. For example, an information classification system disclosed in Non-Patent Document 1 classifies information based on entropy (the amount of information).
Further, an information classification system disclosed in Non-Patent Document 2 stores classified information already classified in a certain group and group specification information for specifying the group in association with each other. With respect to each of group specification information different from each other among the stored group specification information, the information classification system selects one of classified information stored in association with the group specification information, as reference information. A process by which the information classification system selects reference information is also called offline phase.
The information classification system acquires unclassified information, which is the target of classification. Based on the acquired unclassified information and the selected reference information, the information classification system specifies a group into which the unclassified information should be classified. A process by which the information classification system classifies unclassified information is also called online phase.    [Non-Patent Document 1] Shane Robert Cloude, Eric Pottier, “An Entropy Based Classification Scheme for Land Applications of Polarimetric SAR,” IEEE, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, January 1997, Volume 35, No. 1, pp. 68-78    [Non-Patent Document 2] Ali Taheri, Arvinder Singh, Emmanuel Agu, “Location Fingerprinting on Infrastructure 802.11 Wireless Local Area Networks Location Fingerprinting on Infrastructure 802.11 Wireless Local Area Network,” IEEE, 29th Annual IEEE International Conference on Local Computer Networks (LCN'04), 2004, pp 676-683
In the information classification system described above, it is impossible to acquire a value depending on a probability that a group specified as a group into which unclassified information should be classified is a true (correct) group. Therefore, the information classification system described above has a problem that it is impossible to execute a different process in accordance with the probability.